Model Fine-Tuning & Training: Fine-tune Large Language Models (LLMs) to optimize their performance for specific tasks and improve overall model accuracy.
Model Deployment: Deploy generative AI models into production environments using cloud platforms (Azure, AWS)and containerization technologies such as Docker.
Cloud Integration: Design and implement end-to-end AI solutions using services from Azure or AWS Marketplace, including but not limited to Cognitive Services, Object Storage, API Management (APIM), and App Services.
NLP & Search Solutions: Implement NLP-based solutions and develop indexing/search capabilities, with in-depth experience in at least one iindexing systems.
API Development: Build and maintain RESTful APIs using frameworks like Flask or FastAPI to serve AI models and integrate them with external systems.
LLM Evaluation & Agentic AI:Evaluate the performance of LLMs for varioususe cases and explore the potential of agentic AI to improve system efficiency.
Continuous Learning & Research: Stay up-to-date with the latest advancements in Generative AI, NLP, and related fields, and incorporate these advancements into the development process
Preferred Skills
Familiarity with other cloud-based tools and services for AI and ML development
Knowledge of best practices for deploying AI models at scale
Job Description
Required Skills & Technologies:
Programming Languages: Python
Cloud Platforms: Azure, AWS
AI Frameworks & Tools: Langchain, LangGraph, PyTorch, SpaCy, DSPy
Web Frameworks: Flask, FastAPI
Containerization: Docker
Search & Indexing: Experience with at least one indexer
Additional: MCP, API Development, LLM Evaluation, Agentic AI
